A Memetic Algorithm for multi-objective fixture layout optimization

2014 ◽  
Vol 229 (16) ◽  
pp. 3047-3058 ◽  
Author(s):  
Xue Bai ◽  
Fei Hu ◽  
Gaiyun He ◽  
Bohui Ding
Keyword(s):  
Memetic Algorithm ◽  
Fitness Function ◽  
Optimization Method ◽  
Layout Optimization ◽  
Accurate Solution ◽  
Entropy Method ◽  
Objective Functions ◽  
Multi Objective ◽  
Fixture Layout ◽  
Fixture Layout Optimization

A proper scheme of fixture layout can reduce locating errors of a workpiece. However, a multi-objective fixture layout optimization, involving multiple conflicting objective functions, will lead to much more accurate solution and complex computation. This paper describes a new approach based on Memetic Algorithm (MA) to multi-objective fixture layout optimization, considering both location accuracy and stability. This approach uses an entropy method to obtain the weights of each objective functions, and establishes a fitness function. Then, a MA is developed to properly select the positions of locators to minimize the fitness function. An example illustrates that the new optimization method based on MA can improve the locating precision of a workpiece effectively and efficiently. This method is also suitable for solving a multi-objective fixture layout optimization problem with more objective functions.

Multi-objective optimization of auto-body fixture layout based on an ant colony algorithm

2019 ◽  
Vol 234 (6) ◽  
pp. 1137-1145
Author(s):  
Milad Khodabandeh ◽  
Maryam Ghassabzadeh Saryazdi ◽  
Abdolreza Ohadi
Keyword(s):  
Ant Colony Algorithm ◽  
Pareto Frontier ◽  
Optimization Method ◽  
Layout Optimization ◽  
Ant Colony ◽  
Car Industry ◽  
Multi Objective ◽  
Fixture Layout ◽  
Fixture Layout Optimization ◽  
Auto Body

Fixtures are extensively used in many industries such as the car industry, to locate and constrain the sheet part during the assembly stage. Fixture layout affects on deformation of sheet parts. Therefore, fixture layout optimization is crucial to the accuracy and quality of products. In addition, the number of clamps that uses in the fixture is another important factor that must be considered in fixture design. This article presents a novel fixture layout optimization method by combining multi-objective ant colony algorithm (M-ACO) and the finite element method. The proposed method optimizes the fixture layout and the number of clamps simultaneously as a multi-objective problem. An approximation of Pareto frontier is acquired by the proposed method. The fixture layout for the side reinforcement of a car is optimized using the proposed method. The results show that the proposed approach performs effectively to optimize the auto-body fixture layout.

Particle Swarm Optimization for Integrated Fixture Layout

2015 ◽  
Vol 787 ◽  
pp. 285-290
Author(s):  
D. Elilraja ◽  
Sundaravel Vijayan
Keyword(s):  
Particle Swarm Optimization ◽  
Manufacturing Industry ◽  
Particle Swarm ◽  
Optimization Method ◽  
Layout Optimization ◽  
Work Piece ◽  
Swarm Optimization ◽  
Fixture Layout ◽  
Fixture Layout Optimization ◽  
Supporting Device

Fixture is a work-holding or supporting device used in the manufacturing industry to hold the workpiece. Fixtures are used to securely locate (position in a specific location or orientation) and support the work, ensuring that all parts produced using the fixture will maintain conformity and interchangeability. The location of fixture elements is called as fixture layout. The fixture layout plays major role in the work piece deformation during the machining operation. Hence optimization of fixture layout to minimize the work piece deformation is one of the critical aspects in the fixture design process. Minimization the workpiece deformation which is the objective function in the present work is calculated using Finite Element Method (FEM) and the fixture layout is optimized using Discrete fixture layout optimization method (DFLOM), Continuous fixture layout optimization method (CFLOM) and Integrated fixture layout optimization method (IFLOM).The workpiece deformation is minimum in Particle Swarm Optimization (PSO) based IFLOM is reported for the selected fixture. In this paper the PSO is used as an optimization tool to optimize the workpiece deformation.

An investigation of the effectiveness of fixture layout optimization methods

2002 ◽  
Vol 42 (2) ◽  
pp. 251-263 ◽  
Author(s):  
Subramanian Vallapuzha ◽  
Edward C De Meter ◽  
Shabbir Choudhuri ◽  
Raghunath P Khetan
Keyword(s):  
Optimization Methods ◽  
Layout Optimization ◽  
Fixture Layout ◽  
Fixture Layout Optimization

Multi-Objective Trajectory Optimization of Free-Floating Space Manipulator Using NSGA-II

2015 ◽  
Vol 713-715 ◽  
pp. 800-804 ◽  
Author(s):  
Gang Chen ◽  
Cong Wei ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Bo Yang Yu
Keyword(s):  
Trajectory Optimization ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Joint Space ◽  
Motion Path ◽  
Objective Functions ◽  
Nsga Ii ◽  
Space Manipulator ◽  
Multi Objective

In this paper, a kind of multi-objective trajectory optimization method based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed for free-floating space manipulator. The aim is to optimize the motion path of the space manipulator with joint angle constraints and joint velocity constraints. Firstly, the kinematics and dynamics model are built. Secondly, the 3-5-3 piecewise polynomial is selected as interpolation method for trajectory planning of joint space. Thirdly, three objective functions are established to simultaneously minimize execution time, energy consumption and jerk of the joints. At last, the objective functions are combined with the NSGA-II algorithm to get the Pareto optimal solution set. The effectiveness of the mentioned method is verified by simulations.

Engine-bracket drilling fixture layout optimization for minimizing the workpiece deformation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramachandran T. ◽  
Surendarnath S. ◽  
Dharmalingam R.
Keyword(s):  
Modeling And Simulation ◽  
Elastic Deformation ◽  
Empirical Model ◽  
Layout Optimization ◽  
Optimization Techniques ◽  
Fem Modeling ◽  
Content Type ◽  
Fixture Layout ◽  
Fixture Layout Optimization ◽  
Engine Mount

Purpose Fixture layout design is concerned with immobilization of the workpiece (engine mount bracket) during machining such that the workpiece elastic deformation is reduced. The fixture holds the workpiece through the positioning of fixturing elements that causes the workpiece elastic deformation, in turn, leads to the form and dimensional errors and increased machining cost. The fixture layout has the major impact on the machining accuracy and is the function of the fixturing position. The position of the fixturing elements, key aspects, needed to be optimized to reduce the workpiece elastic deformation. The purpose of this study is to evaluate the optimized fixture layout for the machining of the engine mount bracket. Design Methodology Approach In this research work, using the finite element method (FEM), a model is developed in the MATLAB for the fixture-workpiece system so that the workpiece elastic deformation is determined. The artificial neural network (ANN) is used to develop an empirical model. The results of deformation obtained for different fixture layouts from FEM are used to train the ANN and finally the empirical model is developed. The model capable of predicting the deformation is embedded to the evolutionary optimization techniques, capable of finding local and global optima, to optimize the fixture layouts and to find the robust one. Findings For efficient optimization of the fixture layout parameters to obtain the least possible deformation, ant colony algorithm (ACA) and artificial bee colony algorithm (ABCA) are used and the results of deformation obtained from both the optimization techniques are compared for the best results. Research Limitations Implications A MATLAB-based FEM technique is able to provide solutions when the repeated modeling and simulations required i.e. modeling of fixture layouts (500 layouts) for every variation in the parameters requires individual modeling and simulation for the output requirement in any FEM-based software’s (ANSYS, ABACUS). This difficulty is reduced in this research. So that the MATLAB-based FEM modeling, simulation and optimization is carried out to determine the solutions for the optimized fixture layout to reach least deformation. Practical Implications Many a time the practicability of the machining/mechanical operations are difficult to perform costly and time-consuming when more number of experimentations are required. To sort out the difficulties the computer-based automated solution techniques are highly required. Such kind of research over this study is presented for the readers. Originality Value A MATLAB-based FEM modeling and simulation technique is used to obtain the fixture layout optimization. ANN-based empirical model is developed for the fixture layout deformation that creates a hypothesis for the fixture layout system. ACA and ABCA are used for optimizing the fixture layout parameters and are compared for the best algorithm suited for the fixture layout system.

Fixture Layout Design of Sheet Metal Parts Based on Global Optimization Algorithms

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
YanFeng Xing
Keyword(s):  
Finite Element ◽  
Global Optimization ◽  
Sheet Metal ◽  
Optimization Algorithms ◽  
Layout Optimization ◽  
Sheet Metal Parts ◽  
Fixture Layout ◽  
Fixture Layout Optimization ◽  
Dimensional Variation

Fixture layout can affect deformation and dimensional variation of sheet metal assemblies. Conventionally, the assembly dimensions are simulated with a quantity of finite element (FE) analyses, and fixture layout optimization needs significant user intervention and unaffordable iterations of finite element analyses. This paper therefore proposes a fully automated and efficient method of fixture layout optimization based on the combination of 3dcs simulation (for dimensional analyses) and global optimization algorithms. In this paper, two global algorithms are proposed to optimize fixture locator points, which are social radiation algorithm (SRA) and GAOT, a genetic algorithm (GA) in optimization toolbox in matlab. The flowchart of fixture design includes the following steps: (1) The locating points, the key elements of a fixture layout, are selected from a much smaller candidate pool thanks to our proposed manufacturing constraints based filtering methods and thus the computational efficiency is greatly improved. (2) The two global optimization algorithms are edited to be used to optimize fixture schemes based on matlab. (3) Since matlab macrocommands of 3dcs have been developed to calculate assembly dimensions, the optimization process is fully automated. A case study of inner hood is applied to demonstrate the proposed method. The results show that the GAOT algorithm is more suitable than SRA for generating the optimal fixture layout with excellent efficiency for engineering applications.

scholarly journals Problems of a Utopia Point Setting in Transformation of Individual Objective Functions in Multi-Objective Optimization

2019 ◽  
Vol 27 (45) ◽  
pp. 64-71
Author(s):  
Pavel Važan ◽  
Zuzana Červeňanská ◽  
Janette Kotianová ◽  
Jiří Holík
Keyword(s):  
Production Control ◽  
A Priori ◽  
Optimization Method ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Weighted Sum Method ◽  
The Individual ◽  
Utopia Point

Abstract In an optimal processes control, where the considered goals are in general observed as concurrently conflicted, a multi-objective approach fits the best. Commonly used scalarization techniques in multi-objective optimization need a transformation of the individual single-objective functions involved into a scalar multi-criteria objective function. There are many parameters which can influence the optimization results solutions, including an unreachable utopia point value. In this study, the authors compare the multi-objective problem solutions found via two ways of the individual objectives transformation with the respect to setting the utopia point. The methods are used in the area of production control in a case study for a batch production system. To find the solutions, The Weighted Sum Method with a priori articulated preferences under specific constraints as the scalar multi-objective optimization method is applied in simulation optimization.

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